B. Previous Studies In a meta-analysis of three prospective cohorts--Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study--in 13,685 white people of European descent as part of the QTGEN consortium, Newton-Cheh and colleagues identified common variant associations (p < 5x10-8) at five loci previously associated with QT interval: NOS1AP, KCNQ1, KCNE1, KCNH2, and SCN5A, as well as new associations in 5 other loci previously unrecognized to influence myocardial repolarization10. At these 10 loci, 14 independent variants explained 5.4 - 6.5% of the variation of the QT interval, which was more than is explained by sex or age, the strongest non-genetic clinical factors10. A QT genotype score based on these variants was associated with a 9.7 - 12.4ms longer QTc in the top quintile compared with the bottom quintile in the meta-analysis samples, which included heterogeneous age, risk factor and drug exposure profiles10-12. These effects were consistent in individuals of both European and African American ancestry. This QT score was independently validated in a Finnish population sample in which complete medication ascertainment enabled excluding those on QT-altering therapy, and in which the QT score was associated with a 15.6ms QT interval difference between the top and bottom quintiles13. In this analysis, the correlation of the measured effect estimates to those of the original association study from which they were obtained was 0.99. The QT based on the genotype score was a significant predictor of the actual QT interval measured (P < 10-107). This study is important for the current proposal because a) it demonstrates the consistency of genetic effect estimates derived from meta-analysis of heterogeneous studies when applied to independent samples and b) it confirms that excluding individuals with QT-altering drug therapy can reduce the noise from non-genetic sources of QT variation and improve the genetic signal and thereby increase power.